{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "`Learn the Basics <intro.html>`_ ||\n",
    "`Quickstart <quickstart_tutorial.html>`_ || \n",
    "`Tensors <tensorqs_tutorial.html>`_ || \n",
    "`Datasets & DataLoaders <data_tutorial.html>`_ ||\n",
    "`Transforms <transforms_tutorial.html>`_ ||\n",
    "`Build Model <buildmodel_tutorial.html>`_ ||\n",
    "`Autograd <autogradqs_tutorial.html>`_ ||\n",
    "**Optimization** ||\n",
    "`Save & Load Model <saveloadrun_tutorial.html>`_\n",
    "\n",
    "Optimizing Model Parameters 自动微分属于优化器，优化器包含自动微分这功能\n",
    "===========================\n",
    "\n",
    "Now that we have a model and data it's time to train, validate and test our model by optimizing its parameters on \n",
    "our data. Training a model is an iterative process; in each iteration (called an *epoch*) the model makes a guess about the output, calculates \n",
    "the error in its guess (*loss*), collects the derivatives of the error with respect to its parameters (as we saw in \n",
    "the `previous section  <autograd_tutorial.html>`_), and **optimizes** these parameters using gradient descent. For a more \n",
    "detailed walkthrough of this process, check out this video on `backpropagation from 3Blue1Brown <https://www.youtube.com/watch?v=tIeHLnjs5U8>`__.\n",
    "\n",
    "Prerequisite Code \n",
    "-----------------\n",
    "We load the code from the previous sections on `Datasets & DataLoaders <data_tutorial.html>`_ \n",
    "and `Build Model  <buildmodel_tutorial.html>`_.\n",
    "\n",
    "![image.png](attachment:image.png)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch \n",
    "from torch import nn #编写网络结构包\n",
    "from torch.utils.data import DataLoader#数据集及数据加载器\n",
    "from torchvision import datasets\n",
    "from torchvision.transforms import ToTensor, Lambda #Pil图片数据或numpy的narray数据转化为张量\n",
    "\n",
    "training_data = datasets.FashionMNIST(\n",
    "    root=\"data\",#下载数据集到这个文件夹\n",
    "    train=True,#训练集\n",
    "    download=True,\n",
    "    transform=ToTensor()#数据转化为Tensor\n",
    ")\n",
    "\n",
    "test_data = datasets.FashionMNIST(\n",
    "    root=\"data\",\n",
    "    train=False,#测试集\n",
    "    download=True,\n",
    "    transform=ToTensor()#标签转化为Tensor\n",
    ")\n",
    "\n",
    "train_dataloader = DataLoader(training_data, batch_size=64)#方便模式输入层接受\n",
    "test_dataloader = DataLoader(test_data, batch_size=64)#方便模式输入层接受\n",
    "\n",
    "class NeuralNetwork(nn.Module):#子类继承nn类来编写神经网络\n",
    "    def __init__(self):\n",
    "        super(NeuralNetwork, self).__init__()\n",
    "        self.flatten = nn.Flatten()\n",
    "        self.linear_relu_stack = nn.Sequential(\n",
    "            nn.Linear(28*28, 512),\n",
    "            nn.ReLU(),\n",
    "            nn.Linear(512, 512),\n",
    "            nn.ReLU(),\n",
    "            nn.Linear(512, 10),#最后输出10类\n",
    "            nn.ReLU()\n",
    "        )\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = self.flatten(x) #扁平到一维数组方便模型输入层食用\n",
    "        logits = self.linear_relu_stack(x)\n",
    "        return logits\n",
    "\n",
    "model = NeuralNetwork()"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hyperparameters \n",
    "-----------------\n",
    "\n",
    "Hyperparameters are adjustable parameters that let you control the model optimization process. \n",
    "Different hyperparameter values can impact model training and convergence rates \n",
    "(`read more <https://pytorch.org/tutorials/beginner/hyperparameter_tuning_tutorial.html>`__ about hyperparameter tuning)\n",
    "\n",
    "We define the following hyperparameters for training:\n",
    " - **Number of Epochs** - the number times to iterate over the dataset\n",
    " - **Batch Size** - the number of data samples propagated through the network before the parameters are updated\n",
    " - **Learning Rate** - how much to update models parameters at each batch/epoch. Smaller values yield slow learning speed, while large values may result in unpredictable behavior during training.\n",
    "![image.png](attachment:image.png)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "learning_rate = 1e-3\n",
    "batch_size = 64\n",
    "epochs = 5"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)\n",
    "Optimization Loop\n",
    "-----------------\n",
    "\n",
    "Once we set our hyperparameters, we can then train and optimize our model with an optimization loop. Each \n",
    "iteration of the optimization loop is called an **epoch**. \n",
    "\n",
    "Each epoch consists of two main parts:\n",
    " - **The Train Loop** - iterate over the training dataset and try to converge to optimal parameters.\n",
    " - **The Validation/Test Loop** - iterate over the test dataset to check if model performance is improving.\n",
    "\n",
    "Let's briefly familiarize ourselves with some of the concepts used in the training loop. Jump ahead to \n",
    "see the `full-impl-label` of the optimization loop.\n",
    "\n",
    "Loss Function\n",
    "~~~~~~~~~~~~~~~~~\n",
    "\n",
    "When presented with some training data, our untrained network is likely not to give the correct \n",
    "answer. **Loss function** measures the degree of dissimilarity of obtained result to the target value, \n",
    "and it is the loss function that we want to minimize during training. To calculate the loss we make a \n",
    "prediction using the inputs of our given data sample and compare it against the true data label value.\n",
    "\n",
    "Common loss functions include `nn.MSELoss <https://pytorch.org/docs/stable/generated/torch.nn.MSELoss.html#torch.nn.MSELoss>`_ (Mean Square Error) for regression tasks, and \n",
    "`nn.NLLLoss <https://pytorch.org/docs/stable/generated/torch.nn.NLLLoss.html#torch.nn.NLLLoss>`_ (Negative Log Likelihood) for classification. \n",
    "`nn.CrossEntropyLoss <https://pytorch.org/docs/stable/generated/torch.nn.CrossEntropyLoss.html#torch.nn.CrossEntropyLoss>`_ combines ``nn.LogSoftmax`` and ``nn.NLLLoss``.\n",
    "\n",
    "We pass our model's output logits to ``nn.CrossEntropyLoss``, which will normalize the logits and compute the prediction error.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Initialize the loss function\n",
    "loss_fn = nn.CrossEntropyLoss()"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Optimizer\n",
    "\n",
    "~~~~~~~~~~~~~~~~~\n",
    "\n",
    "Optimization is the process of adjusting model parameters to reduce model error in each training step. **Optimization algorithms** define how this process is performed (in this example we use Stochastic Gradient Descent).\n",
    "All optimization logic is encapsulated in  the ``optimizer`` object. Here, we use the SGD optimizer; additionally, there are many `different optimizers <https://pytorch.org/docs/stable/optim.html>`_ \n",
    "available in PyTorch such as ADAM and RMSProp, that work better for different kinds of models and data.\n",
    "\n",
    "We initialize the optimizer by registering the model's parameters that need to be trained, and passing in the learning rate hyperparameter.\n",
    "![image.png](attachment:image.png)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# optimizer = torch.optim.SGD(model.parameters(), lr=learning_rate)"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Inside the training loop, optimization happens in three steps:\n",
    " * Call ``optimizer.zero_grad()`` to reset the gradients of model parameters. Gradients by default add up; to prevent double-counting, we explicitly zero them at each iteration.\n",
    " * Backpropagate the prediction loss with a call to ``loss.backwards()``. PyTorch deposits the gradients of the loss w.r.t. each parameter. \n",
    " * Once we have our gradients, we call ``optimizer.step()`` to adjust the parameters by the gradients collected in the backward pass.  \n",
    "\n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "Full Implementation\n",
    "-----------------------\n",
    "We define ``train_loop`` that loops over our optimization code, and ``test_loop`` that \n",
    "evaluates the model's performance against our test data.\n",
    "\n",
    "![image.png](attachment:image.png)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def train_loop(dataloader, model, loss_fn, optimizer):\n",
    "    size = len(dataloader.dataset)\n",
    "    for batch, (X, y) in enumerate(dataloader):        \n",
    "        # Compute prediction and loss\n",
    "        pred = model(X)\n",
    "        loss = loss_fn(pred, y)\n",
    "        \n",
    "        # Backpropagation\n",
    "        optimizer.zero_grad()\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "\n",
    "        if batch % 100 == 0:\n",
    "            loss, current = loss.item(), batch * len(X)\n",
    "            print(f\"loss: {loss:>7f}  [{current:>5d}/{size:>5d}]\")\n",
    "\n",
    "\n",
    "def test_loop(dataloader, model, loss_fn):\n",
    "    size = len(dataloader.dataset)\n",
    "    num_batches = len(dataloader)\n",
    "    test_loss, correct = 0, 0\n",
    "\n",
    "    with torch.no_grad(): #只预测不用去计算梯度\n",
    "        for X, y in dataloader:\n",
    "            pred = model(X)\n",
    "            test_loss += loss_fn(pred, y).item()\n",
    "            correct += (pred.argmax(1) == y).type(torch.float).sum().item()\n",
    "            \n",
    "    test_loss /= num_batches\n",
    "    correct /= size\n",
    "    print(f\"Test Error: \\n Accuracy: {(100*correct):>0.1f}%, Avg loss: {test_loss:>8f} \\n\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We initialize the loss function and optimizer, and pass it to ``train_loop`` and ``test_loop``.\n",
    "Feel free to increase the number of epochs to track the model's improving performance.\n",
    "\n",
    "\n",
    "我们初始化损失函数和优化器，并将其传递给train_loop和test_loop。随意增加 epochs 的数量以跟踪模型的改进性能。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "loss_fn = nn.CrossEntropyLoss()\n",
    "optimizer = torch.optim.SGD(model.parameters(), lr=learning_rate)\n",
    "\n",
    "epochs = 10\n",
    "for t in range(epochs):\n",
    "    print(f\"Epoch {t+1}\\n-------------------------------\")\n",
    "    train_loop(train_dataloader, model, loss_fn, optimizer)\n",
    "    test_loop(test_dataloader, model, loss_fn)\n",
    "print(\"Done!\")#运行没问题"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Further Reading\n",
    "-----------------------\n",
    "- `Loss Functions <https://pytorch.org/docs/stable/nn.html#loss-functions>`_\n",
    "- `torch.optim <https://pytorch.org/docs/stable/optim.html>`_\n",
    "- `Warmstart Training a Model 热启动训练模型<https://pytorch.org/tutorials/recipes/recipes/warmstarting_model_using_parameters_from_a_different_model.html>`_\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "display_name": "Python 3",
   "language": "python",
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    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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   "pygments_lexer": "ipython3",
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